The Subjecthood of Slime Mould: modelling single-celled intelligence through living systems art
This PhD by Published Work presents a body of artistic research created by Heather Barnett working with the slime mould, Physarum polycephalum, a single-celled amoeba employed as a model organism within a wide range of disciplinary domains.
Barnett, Heather
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Multi-objective optimization of hybrid microgrid for energy trilemma goals using slime mould algorithm. [PDF]
Shrivastav AK, Dutta S.
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Machine learning based prediction of carbon concentration in carburized steel. [PDF]
Zhang Y, Tang Z, Yin Q, Wang Y, Nie Z.
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Novel SMA BASED Elmanspiking neural network modelled fuzzy PI controller for speed-torque regulation of PMSM. [PDF]
Natarajan L +3 more
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Method for predicting dynamic current-carrying capacity of transmission lines by integrating improved VMD and time-varying ensemble model. [PDF]
Yang S, Hao W.
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Fault diagnosis using ISMA to optimize SVM parameters for aircraft engine damage repair. [PDF]
Xue P, Yu J, Zhang H.
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Dung Beetle with Reflection Cuckoo Catfish Optimizer for Numerical Optimization and Reservoir Production Optimization. [PDF]
Li S, Yin T.
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Optimizing the allocation of renewable DGs, DSTATCOM, and BESS to mitigate the impact of electric vehicle charging stations on radial distribution systems. [PDF]
T Y +4 more
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Comprehensive Learning Fungal Growth Optimizer for Numerical Optimization and Reservoir Production Optimization. [PDF]
Gong M, Song Z, Zhang X, Tang Y.
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A two-stage multi-objective optimization framework for coordinated EV charging scheduling and reactive power dispatch. [PDF]
Badr MS, Sharaf HM, Zobaa AM.
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